Stage GAI use in assessment: permit exploration, restrict independent reasoning, require justification¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article prescribes concrete ethical boundaries for GAI use within LEARN-informed assessment. GAI 'may be used for exploratory purposes such as brainstorming, generating alternative perspectives, receiving formative feedback, or testing assumptions', but 'should be restricted when tasks require independent interpretation of evidence, final causal reasoning, personal reflection, or demonstration of disciplinary judgement'. Ethical use is operationalised through transparent documentation: AI-use logs, prompt records, reflective justification, and disclosure of AI assistance.

Design Implications¶

Context¶

Requirements¶

• Transparent documentation including AI-use logs, prompt records, and reflective justification of how AI outputs were evaluated and transformed

Constraints¶

• Submitting unmodified AI-generated work, fabricating sources, concealing AI assistance, or relying on AI to replace required reasoning are considered inappropriate uses

Target Learners¶

• higher education students

Target Learning Goals¶

• ethical AI use
• independent reasoning
• academic integrity

Affordances¶

• Learn Framework Gai Assessment

Related Strategies¶

• Institutional recommendations: shift from detection to process-oriented assessment, transparent AI-use protocols, and revised integrity policies
• Replace detector-centred assessment with a four-stage process-oriented model: declared starting point, versioned drafting, process artefacts, and targeted oral verification
• Pair AI-permitted take-home assignments with supervised modifications, oral defense, prediction, and transfer tasks to verify understanding
• Define and Apply Ethical Responsibility
• Apply an affective data governance framework: minimization, purpose limitation, consent, human oversight, and separation from evaluation
• Assessment design levers that make learning visible and reduce the payoff from generic generated text
• Graduate the AI policy across the curriculum so that permitted AI use tracks each course's pedagogical purpose

Examples¶

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Key Sources¶

• Lorna Uden · Gwo-Jen Hwang. (2026). The LEARN framework for responsible use of generative AI in education: a neuroscience-informed model for problem-based learning. Journal of Computers in Education. https://doi.org/10.1007/s40692-026-00398-x